Cursor インストールガイド
開発者向け MCP サーバーとよく使われる AI コードエディタ。
MCP Servers
MCP server that gives any LLM its own computer — managed Docker workspaces with live browser, terminal, code execution, document skills, and autonomous sub-agents.
Specialized bridge designed to connect LLMs and AI agents directly to Siemens SIMATIC TIA Portal V21.
Local-first knowledge compiler for humans and agents. Inspired by Karpathy's vision. Plain markdown, CLI + MCP server.
Local macOS control server for MCP clients and Custom GPT Actions
Git-native API client with encrypted secrets.
Secrets management for AI agents via MCP • @janeesecure
Reliability gateway for AI tool output: schema-stable, secret-safe, pagination-complete JSON for MCP and CLI agents.
A self-modifying, self-verifying AI agent with persistent state. Reads its own source code. Plans changes. Tests them in a sandbox before applying.
Four small MCP tools that let apfel (Apple's on-device LLM) reach the web and read local files: url-fetch (read a page), ddg-search (web search), search-and-fetch (search+read in one call), fs...
Add vision to text-only models in Opencode (, ) — , no manual file saving.
This project is . Please provide feedback via GitHub issues.
An MCP server that provides access to LLMs using the LlamaIndexTS library.
Agent Skills
The Best AI Agent Framework for Agent Collaboration.
The open sharing protocol for the agentic era. A Linux Foundation AI & Data Project
Agent Skills
- : Turn your idea into a video using your coding agent. - : Edit and animate using drag and drop. - : Connect to data, and manage complexity with code.
Reverse-engineer any design system into a Claude-ready skill. Pure static analysis. No AI. No API keys.
Craft AI-driven interface effortlessly🤖
Official Pulumi Agent Skills for writing, migrating, and operating infrastructure with AI coding agents
- [2026/05/01] 🔥 (📃Paper) has been released.
A Claude Code of the skills we share at AI Builder Club for building : agents that get triggered on their own, pick up work, ship it, verify it, and log what they learned, so the work compounds...
"To achieve great things, two things are needed: a plan and not quite enough time." - attributed to Leonard Bernstein
Commonplace studies how agentic systems can change after deployment through inspectable knowledge artifacts.
LiteRT-LM is Google's production-ready, high-performance, open-source inference framework for deploying Large Language Models on edge devices.